1. Field of the Invention
This invention is related to seismic data processing. More specifically, the invention is related to a system for processing seismic data to detect azimuthal velocity variations.
2. Description of Related Art
Seismic surveys are routinely used in the search for oil and gas reservoirs in the earth's subsurface. Seismic surveys are performed by imparting acoustic energy into the earth, either at a land surface or in a marine environment, and then detecting the reflected and refracted acoustic energy. The delay time between the imparting of the acoustic energy wave at the source location and detection of the same wave at a receiver location indicates the depth of reflecting geological interfaces.
Until recently, only two-dimensional (“2D”) seismic surveys were conducted, with the seismic source locations being collinear with a line of receivers. Recent advances in technology have enabled three-dimensional (“3D”) seismic survey data to be gathered and analyzed. Typically, in 3D surveys arrays of seismic receivers are deployed which receive reflected acoustic energy imparted at varying locations that may be specifically selected to provide a rich assortment of azimuths for common midpoints.
A technique frequently used in seismic survey analysis is AVO analysis, which is the amplitude variation with offset, and is also referred to herein as amplitude variation with incidence angle. According to the AVO approach, attributes of a subsurface interface are determined both from the normal-incidence amplitude of reflected seismic energy, and also from the dependence of the detected seismic reflections on the angle of incidence of the seismic energy at a subsurface reflecting interface relative to the vertical. In conventional AVO analysis, multiple seismic traces having a common reflection point, commonly referred to as a common mid point or common depth point(CMP or CDP) gather, are collected. From the CMP (or CDP) gather, one may derive the amplitude R of a reflected seismic wave from an interface (i.e., the “target horizon”) as a function of the angle of incidence θ from the normal according to the following relationship:R(θ)=A+B sin2 θ. In this case, the coefficient A is the zero-offset response (also referred to as the AVO intercept), while the coefficient B is referred to as the AVO slope, or gradient, as it is representative of the rate of change of amplitude with the square of the angle of incidence. Analysis of the AVO slope and intercept can provide indicators of interesting formations, from an oil and gas exploration standpoint. For example, variations in the A and B values from a theoretical A-versus-B trend line for the expected stratigraphic sequences can indicate the location of hydrocarbon reserves.
While simple models of subsurface geology assume azimuthal isotropy in the propagation of acoustic energy it has been observed that azimuthal anisotropy is in fact present in many survey regions, such that the velocity of acoustic energy depends upon the azimuth of the source-receiver path. If azimuthal anisotropy is present, the conventional normal moveout correction may not adequately align the seismic traces in the gather, which can result in degraded AVO analysis.
Normal moveout correction of the seismic data, both for offset-dependent delays and also for azimuthal anisotropy caused by the overburden, is therefore typically performed in producing stacked traces of improved signal-to-noise ratio for use in a 3D seismic survey. For example, U. S. Pat. No. 5,532,978 describes a method of deriving and applying azimuthal anisotropy corrections to seismic survey signals.
The detection of a preferred azimuthal direction at a reflecting interface can also provide important information regarding geological features. For example, a preferred azimuthal reflection direction can indicate the presence of aligned vertical fractures. For moderately far offsets (25°-35° incidence angles), the P-wave traveling in the plane wave parallel to aligned vertical fractures has a higher velocity than the P-wave traveling in the plane perpendicular to the fractures.
Traditionally, azimuthal velocity analysis has been performed using azimuth-sectored supergathers and picking semblance maxima at various azimuths. This reduces the problem to a series of 2-D solutions, rather than solving the complete 3-D solution. In some cases as few as two sectors may be chosen, perpendicular and parallel to the (average) principal axes of the azimuthal anisotropy. If more than two sectors are used, an ellipse is fitted to the picked velocities to give fast and slow velocity magnitudes and the azimuth of the fast velocity. These procedures suffer from several drawbacks:
Picking semblance, by hand, on azimuth sectored data is processor/interpreter dependent and extremely time consuming.
Semblance works well for data which do not show amplitude variation with offset (“AVO”), however, if the data contain significant AVO, particularly if there is a polarity reversal, semblance can fail. In this case automatic picking of semblance maxima will be erroneous.
If the subsurface has azimuthal velocity variation (“AVV”) then this will appear as an offset-dependent static viewed on offset-sorted CMP gathers. This will reduce the effectiveness of any surface consistent statics solution, thus the azimuth-sectored supergathers will most likely be contaminated with statics. This will significantly degrade the semblance analysis and may result in several semblance maxima.
The semblance is based on giving the greatest stack power. However, for AVV analysis it is the actual subsurface velocity that is of interest, not simply the velocity that gives the best stack. For instance, if a higher amplitude occurs at a particular azimuth within the sector, then the velocity at that azimuth will be picked. In addition, if those high amplitudes are at the mid to near offsets and are contaminated with residual statics then a completely erroneous velocity could give the highest semblance.
Sectoring and partial stacking of the data means that it is extremely difficult to obtain error estimates. Not only is it difficult to attribute a picking error from picking semblance, but errors due to the acquisition geometry are not represented. In any analysis of this type it is important to compute the errors associated with the obtained results. For instance a weighted least squares approach has been used to compute the errors in a technique for inverting azimuthal variation of amplitude for shear wave data. It has also been observed that the reliability of the amplitude variation with azimuth analysis has been assessed by looking for an absence of the acquisition geometry being mirrored in the anisotropy maps.
It should be noted that the description of the invention which follows should not be construed as limiting the invention to the examples and preferred embodiments shown and described. Those skilled in the art to which this invention pertains will be able to devise variations of this invention within the scope of the appended claims.